Huge Automatically Extracted Training Sets for Multilingual Word Sense Disambiguation

May 12, 2018 ยท Declared Dead ยท ๐Ÿ› International Conference on Language Resources and Evaluation

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Authors Tommaso Pasini, Francesco Maria Elia, Roberto Navigli arXiv ID 1805.04685 Category cs.CL: Computation & Language Citations 8 Venue International Conference on Language Resources and Evaluation Last Checked 5 months ago
Abstract
We release to the community six large-scale sense-annotated datasets in multiple language to pave the way for supervised multilingual Word Sense Disambiguation. Our datasets cover all the nouns in the English WordNet and their translations in other languages for a total of millions of sense-tagged sentences. Experiments prove that these corpora can be effectively used as training sets for supervised WSD systems, surpassing the state of the art for low-resourced languages and providing competitive results for English, where manually annotated training sets are accessible. The data is available at trainomatic.org.
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